class_docstr: Model architecture from:
  https://adventuresinmachinelearning.com/pytorch-tutorial-deep-learning/
class_docstr_tok: ["Model","architecture","from",":","https",":","\/\/adventuresinmachinelearning.com\/pytorch-tutorial-deep-learning\/"]
code: def __init__(
      self, num_in, num_hidden, num_out, inplace=False
  ) -> None:
      super().__init__()
      self.num_in = num_in
      self.num_hidden = num_hidden
      self.num_out = num_out
      self.lin1 = nn.Linear(num_in, num_hidden)
      self.lin2 = nn.Linear(num_hidden, num_hidden)
      self.lin3 = nn.Linear(num_hidden, num_out)
      self.relu1 = nn.ReLU(inplace=inplace)
      self.relu2 = nn.ReLU(inplace=inplace)
      self.softmax = nn.Softmax(dim=1)
  
file_path: captum/tests/helpers/classification_models.py
imports: import torch
  import torch.nn
label_desc: Use image node_id 1 to create a new SoftmaxModel object from inherited base classes: nn with example: obj = SoftmaxModel(num_in, num_hidden, num_out, inplace)